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Published on: June 30, 2014
Plateau of practice effects and noise with repeat SDMT testing in multiple sclerosis
Lenka Novakova1,2, Igal Rosenstein1,2, Markus Axelsson1,2
1Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Practice effects for the Symbol Digit Modalities Test (SDMT) plateau after 18 administrations in people with multiple sclerosis. High-frequency testing did not improve cognitive decline detection, highlighting the need for alternate SDMT versions.
Area of Science:
- Neuroscience
- Clinical Psychology
- Rehabilitation Medicine
Background:
- The Symbol Digit Modalities Test (SDMT) is a primary cognitive assessment for multiple sclerosis (MS).
- Repeated SDMT administration is subject to practice effects and test-retest variability, complicating longitudinal tracking of cognitive function in people with MS (PwMS).
Purpose of the Study:
- To quantify the build-up and plateau of SDMT practice effects with high-frequency testing.
- To establish reliable cutoffs for detecting longitudinal cognitive change in PwMS.
- To determine if increased testing frequency enhances the detection of cognitive decline.
Main Methods:
- PwMS underwent monthly SDMT testing over three years.
- Plateau regression analysis identified practice effect inflection points.
- Reliable change was assessed, and findings were compared to a low-density testing group.
Main Results:
- Practice effects on the SDMT plateaued after 18 administrations (p < 0.001).
- A minimum 7-point change in SDMT score was required for 90% confidence in detecting cognitive decline.
- Increased testing frequency did not significantly improve the detection of cognitive decline (p = 0.256).
Conclusions:
- Practice effects in the SDMT are substantial, requiring up to 18 administrations to stabilize.
- Test-retest variability observed is consistent with existing literature.
- Findings necessitate the use of alternate SDMT forms and reliable change methodologies for accurate cognitive monitoring in PwMS.
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